Exclusion rules, bottlenecks and the evolution of stochastic phenotype switching

Stochastic phenotype switching—often considered a bet hedging or risk-reducing strategy—can enhance the probability of survival in fluctuating environments. A recent experiment provided direct evidence for an adaptive origin by showing the de novo evolution of switching in bacterial populations propagated under a selective regime that captured essential features of the host immune response. The regime involved strong frequency-dependent selection realized via dual imposition of an exclusion rule and population bottleneck. Applied at the point of transfer between environments, the phenotype common in the current environment was assigned a fitness of zero and was thus excluded from participating in the next round (the exclusion rule). In addition, also at the point of transfer, and so as to found the next bout of selection, a single phenotypically distinct type was selected at random from among the survivors (the bottleneck). Motivated by this experiment, we develop a mathematical model to explore the broader significance of key features of the selective regime. Through a combination of analytical and numerical results, we show that exclusion rules and population bottlenecks act in tandem as potent selective agents for stochastic phenotype switching, such that even when initially rare, and when switching engenders a cost in Malthusian fitness, organisms with the capacity to switch can invade non-switching populations and replace non-switching types. Simulations demonstrate the robustness of our findings to alterations in switching rate, fidelity of exclusion, bottleneck size, duration of environmental state and growth rate. We also demonstrate the relevance of our model to a range of biological scenarios such as bacterial persistence and the evolution of sex.

[1]  S. Majumdar,et al.  Switching and growth for microbial populations in catastrophic responsive environments. , 2009, Biophysical journal.

[2]  Carl T. Bergstrom,et al.  The fitness value of information , 2005, Oikos.

[3]  M. Nowak,et al.  Adaptive evolution of highly mutable loci in pathogenic bacteria , 1994, Current Biology.

[4]  Oscar P. Kuipers,et al.  Phenotypic variation in bacteria: the role of feedback regulation , 2006, Nature Reviews Microbiology.

[5]  THEORY OF FITNESS IN A HETEROGENEOUS ENVIRONMENT , 2022 .

[6]  N. Maizels Immunoglobulin gene diversification. , 2005, Annual review of genetics.

[7]  B. Stecher,et al.  A Simple Screen to Identify Promoters Conferring High Levels of Phenotypic Noise , 2008, PLoS genetics.

[8]  P. Swain,et al.  Stochastic Gene Expression in a Single Cell , 2002, Science.

[9]  B. Levin,et al.  Compensatory mutations, antibiotic resistance and the population genetics of adaptive evolution in bacteria. , 2000, Genetics.

[10]  L. Wahl,et al.  Estimating the optimal bottleneck ratio for experimental evolution: the burst-death model. , 2008, Mathematical biosciences.

[11]  D. Dubnau,et al.  Noise in Gene Expression Determines Cell Fate in Bacillus subtilis , 2007, Science.

[12]  J. Pitchford,et al.  Exact Results for the Evolution of Stochastic Switching in Variable Asymmetric Environments , 2010, Genetics.

[13]  R. Lande,et al.  GENOTYPE‐ENVIRONMENT INTERACTION AND THE EVOLUTION OF PHENOTYPIC PLASTICITY , 1985, Evolution; international journal of organic evolution.

[14]  Carl T. Bergstrom,et al.  Phenotypic diversity as an adaptation to environmental uncertainty , 2008 .

[15]  M. Slatkin Hedging one's evolutionary bets , 1974, Nature.

[16]  Joel P. Brockman,et al.  What is Bet-Hedging , 1987 .

[17]  H. J. Beaumont,et al.  Experimental evolution of bet hedging , 2009, Nature.

[18]  M. Feldman,et al.  Evolution of Stochastic Switching Rates in Asymmetric Fitness Landscapes , 2009, Genetics.

[19]  Han N. Lim,et al.  A multistep epigenetic switch enables the stable inheritance of DNA methylation states , 2007, Nature Genetics.

[20]  M. Thattai,et al.  Stochastic Gene Expression in Fluctuating Environments , 2004, Genetics.

[21]  S. Leibler,et al.  Phenotypic Diversity, Population Growth, and Information in Fluctuating Environments , 2005, Science.

[22]  C. Pál,et al.  Coevolution with viruses drives the evolution of bacterial mutation rates , 2007, Nature.

[23]  Jerome T. Mettetal,et al.  Stochastic switching as a survival strategy in fluctuating environments , 2008, Nature Genetics.

[24]  S. Leibler,et al.  Bacterial Persistence , 2005, Genetics.

[25]  Adam P Arkin,et al.  A microbial modified prisoner's dilemma game: how frequency-dependent selection can lead to random phase variation. , 2005, Journal of theoretical biology.

[26]  K. Lewis,et al.  Persister cells and tolerance to antimicrobials. , 2004, FEMS microbiology letters.

[27]  A. Arkin,et al.  Diversity in times of adversity: probabilistic strategies in microbial survival games. , 2005, Journal of theoretical biology.

[28]  A. Hoffmann,et al.  Limits to the adaptive potential of small populations , 2006 .

[29]  Carl T. Bergstrom,et al.  Transmission bottlenecks as determinants of virulence in rapidly evolving pathogens. , 1999, Proceedings of the National Academy of Sciences of the United States of America.

[30]  S. Leibler,et al.  Bacterial Persistence as a Phenotypic Switch , 2004, Science.

[31]  Catharine E. Boothroyd,et al.  A yeast-endonuclease-generated DNA break induces antigenic switching in Trypanosoma brucei , 2009 .

[32]  Richard Moxon,et al.  Bacterial contingency loci: the role of simple sequence DNA repeats in bacterial adaptation. , 2006, Annual review of genetics.

[33]  Joanna Masel,et al.  The evolution of bet-hedging adaptations to rare scenarios. , 2007, Theoretical population biology.

[34]  Ivan Saika-Voivod,et al.  Evaluating the impact of population bottlenecks in experimental evolution. , 2002, Genetics.

[35]  L. Partridge,et al.  Oxford Surveys in Evolutionary Biology , 1991 .

[36]  J. A. Halliday,et al.  Transcriptional Infidelity Promotes Heritable Phenotypic Change in a Bistable Gene Network , 2009, PLoS biology.

[37]  George C. Williams,et al.  Sex and evolution. , 1975, Monographs in population biology.

[38]  D. Cohen Optimizing reproduction in a randomly varying environment. , 1966, Journal of theoretical biology.

[39]  A. Sugden ECOLOGY/EVOLUTION: Phenotypic Plasticity , 2004 .

[40]  T. Elston,et al.  Stochasticity in gene expression: from theories to phenotypes , 2005, Nature Reviews Genetics.

[41]  Chin-Yi Chen,et al.  Evidence for a bimodal distribution of Escherichia coli doubling times below a threshold initial cell concentration , 2010, BMC Microbiology.

[42]  F. Andrewes Studies in group-agglutination I. The salmonella group and its antigenic structure† , 1922 .

[43]  B. Levin,et al.  Episodic Selection and the Maintenance of Competence and Natural Transformation in Bacillus subtilis , 2009, Genetics.

[44]  Lauren Ancel Meyers,et al.  Fighting change with change: adaptive variation in an uncertain world , 2002 .

[45]  J. Bull EVOLUTION OF PHENOTYPIC VARIANCE , 1987, Evolution; international journal of organic evolution.